Some Results on the Vector Gaussian Hypothesis Testing Problem

Pierre Escamilla, Abdellatif Zaidi, Michèle A. Wigger

Abstract: This paper studies the problem of discriminating two multivariate Gaussian distributions in a distributed manner. Specifically, it characterizes in a special case the optimal typeII error exponent as a function of the available communication rate. As a side-result, the paper also presents the optimal type-II error exponent of a slight generalization of the hypothesis testing against conditional independence problem where the marginal distributions under the two hypotheses can be different.